Latent Class Analysis

Background: Achieving national reductions in greenhouse gas emissions will require public support for climate and energy policies and changes in population behaviors. Audience segmentation -a process of identifying coherent groups within a population -can be used to improve the effectiveness of public engagement campaigns. Methodology/Principal Findings: In Fall 2008, we conducted a nationally representative survey of American adults (n = 2,164) to identify audience segments for global warming public engagement campaigns. By subjecting multiple measures of global warming beliefs, behaviors, policy preferences, and issue engagement to latent class analysis, we identified six distinct segments ranging in size from 7 to 33% of the population. These six segments formed a continuum, from a segment of people who were highly worried, involved and supportive of policy responses (18%), to a segment of people who were completely unconcerned and strongly opposed to policy responses (7%). Three of the segments (totaling 70%) were to varying degrees concerned about global warming and supportive of policy responses, two (totaling 18%) were unsupportive, and one was largely disengaged (12%), having paid little attention to the issue. Certain behaviors and policy preferences varied greatly across these audiences, while others did not. Using discriminant analysis, we subsequently developed 36-item and 15-item instruments that can be used to categorize respondents with 91% and 84% accuracy, respectively. Conclusions/Significance: In late 2008, Americans supported a broad range of policies and personal actions to reduce global warming, although there was wide variation among the six identified audiences. To enhance the impact of campaigns, government agencies, non-profit organizations, and businesses seeking to engage the public can selectively target one or more of these audiences rather than address an undifferentiated general population. Our screening instruments are available to assist in that process.

The purpose of this study was to develop the yet limited empirical knowledge on the intensity of customer interaction and on specific customer roles in service innovation processes. An empirical study of twelve (12) business service innovation projects was conducted in cleaning and security, financial, and ICT services. We examined both ad hoc and formalised innovation processes. Overall in these service sectors, which offer support services to their customers, direct customer interaction in service development can be characterised as being limited and focused on specific, well-defined tasks. In the analysis, three highly important customer roles emerged: 1. Customers act as catalysts of service development processes. 2. Customer feedback is often decisive in nature, allowing for go/kill decisions and directing other key decisions. 3. Customers have a key role in internal marketing of the new service idea within the provider organisation. We outline a set of questions relating to kn...

Recently, different mixture models have been proposed for multilevel data, generally requiring the local independence assumption. In this work, this assumption is relaxed by allowing each mixture component at the lower level of the hierarchical structure to be modeled according to a multivariate Gaussian distribution with a non-diagonal covariance matrix. For high-dimensional problems, this solution can lead to highly parameterized models. In this proposal, the trade-off between model parsimony and flexibility is governed by assuming a latent factor generative model.

With heightened cultural visibility and greater opportunities for connection, individuals with kinky sexual desires (e.g. BDSM, sexual fetishism, sexual role-playing) are increasingly constructing sexual identities that foreground their kink-oriented desires. However, we know little about how kinky individuals negotiate stigma as they construct sexual identities and engage in intimate practices which provide meaning and coherence to their sense of self. This study examined identity sentiment among an international sample of 265 kink-identified individuals. Participants were asked whether they feel negative, positive, or mixed about their kink identities. An exploratory latent class analysis of narrative data revealed four distinct types of stories: unelaborated affirmation, elaborated affirmation, compartmentalization, and isolation. Stories revealed that stigma, concealment, isolation, and self-pathologization represented sources of stress and negative self-evaluation. Involvement in a kink community and viewing one's kink identity as a journey of growth and exploration were described as helping participants develop resiliency against societal stigma and mental health challenges. Implications of these findings for social psychological theories related to stigma, narrative, and minority stress are discussed.

Background and Aim: Brucellosis remains a globally significant zoonotic disease with significant public health and eco­nomic implications. While domestic pigs are absent in Iraq due to religious restrictions, wild pigs (Sus scrofa) represent a potential reservoir for zoonotic pathogens, including Brucella suis. Despite this, no prior investigations have assessed the prevalence of swine brucellosis in Iraq. This study aimed to (i) determine the seroprevalence of brucellosis in wild pigs using enzyme-linked immunosorbent assay (ELISA), (ii) evaluate associated risk factors such as age, sex, and region, and (iii) con­firm infection and characterize isolates through molecular detection and phylogenetic analysis.

Materials and Methods: Between September 2022 and January 2024, venous blood samples (n = 42) from recently killed wild pigs in Wasit province were analyzed. Sera were screened using ELISA, while DNA was extracted and tested with con­ventional polymerase chain reaction (PCR) and quantitative real-time PCR (qPCR) targeting the 16S ribosomal RNA gene. Positive isolates were sequenced and compared to reference strains in GenBank using phylogenetic analysis. Statistical associations with risk factors were assessed using odds ratios and relative risk.

Results: ELISA detected anti-Brucella antibodies in 54.76% of samples, with mild (39.13%), moderate (34.78%), and severe (26.09%) infections. Molecular assays revealed B. suis DNA in 33.33% of samples by PCR and 45.24% by qPCR. Seropositivity was significantly higher in pigs aged 2–4 years (73.33%) compared with <2 years (38.1%) and >4 years (66.67%) (p < 0.05). Female pigs exhibited a higher prevalence (57.58%) than males (44.44%), and animals from Al-Numaniyah showed the highest rates (73.68%). Phylogenetic analysis revealed 98.87%–99.76% similarity with Indian B. suis strains (MF173089.1), characterized by minor nucleotide variations.

Conclusion: This study provides the first molecular evidence of B. suis in wild pigs in Iraq, underscoring their role as potential reservoirs for zoonotic transmission. The findings highlight the importance of integrating molecular diagnostics with serology for accurate surveillance. Strengthening One Health strategies, including wildlife monitoring, biosecurity, and public health education, is critical to preventing spillover to domestic animals and humans. Further large-scale investiga­tions are warranted to better characterize the epidemiology of swine brucellosis in the region.


Keywords: Brucella suis, Iraq, phylogenetic analysis, quantitative real-time polymerase chain reaction, wild pigs, zoonosis.

Sexual intimate partner violence (SIPV) is a significant public health concern of global importance. This metaanalysis sought to examine the relationship between demographic factors and SIPV perpetration and victimization. Method: The database searches identified a total of 143 articles to be included in the meta-analysis. Comprehensive metaanalysis 3.0 was used to calculate aggregate effect sizes (Pearson's r) for the relationship between demographic variables and SIPV exposure. Variables were examined for SIPV perpetration and victimization and were separated between male and female samples. Results: There was a significant relationship between SIPV victimization and being bisexual (r = .25, p < .001), LGBTQ (r = .21, p < .001), female (r = .19, p < .001), and disabled (r = .19, p < .001). Lower income (r = .07, p = .001), lower education (r = .06, p < .001), and younger age (r = .04, p < .001) also correlated with SIPV victimization. Being married (r =-.08, p = .027) was identified as a protective marker against SIPV victimization. Identifying as female (r =-.17, p = .003) had a negative association with SIPV perpetration. Conclusions: The current study found that several demographic factors are significantly related to increased risk of SIPV perpetration and/or victimization, while few have a protective effect.

Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling.

Objective: To investigate whether behaviors of inattention, hyperactivity, and impulsivity among adolescents in Northern Finland reflect qualitatively distinct subtypes of ADHD, variants along a single continuum of severity, or of severity differences within subtypes. Method: Latent class models, exploratory factor models, and factor mixture models were applied to questionnaire data of ADHD behaviors obtained from the Northern Finland Birth Cohort (NFBC). Latent class models correspond to qualitatively distinct subtypes, factor analysis corresponds to severity differences, and factor mixture analysis allows for both subtypes and severity differences within subtypes. Results: A comparison of the different models shows that models that distinguish between a low scoring majority class (unaffecteds) and a high scoring minority class (affecteds), and allow for two factors (inattentive, hyperactive-impulsive) with severity differences provide the best fit. The analysis provides support that a high-scoring minority group (8.8% of males and 6.8% of females) likely reflects an ADHD group in the Northern Finland Birth Cohort, whereas the majority of the population falls into a low-scoring group of unaffecteds. Distinct factors composed of items of inattention and hyperactivity-impulsivity are evident for both sexes with considerable variability in severity within each class.

This paper addresses the challenge of measuring alignment. Two different approaches are developed: one based on seven dimensions of strategic orientation; and one based on eight dimensions of market orientation. A formula is developed for the calculation of alignment. The formula is applied to a survey of 175 large New Zealand companies. Analyses of the results suggest overall similarity between the strategic orientation and market orientation approaches, yet with distinct differences which might impact on business performance.

Across the linguistically diverse ASEAN (Association of Southeast Asian Nations) member states, English has been acknowledged as the sole official working language. It serves as a unifying medium in business, diplomacy, and education. This study explores emerging assessment practices and methodologies in English language teaching within the regional context over the last five years, considering Kachru's 3 Concentric Circles Model of the English Language. Using databases and following the PRISMA flow, the selected articles were verified by the three experts in English language teaching. A total of 12 published articles met the eligibility criteria: four from Malaysia, four from the Philippines, and four from Indonesia. With Braun and Clarke's thematic analysis steps, key factors influencing English language assessment were identified from the validated studies: benchmarking, learner autonomy, ICT integration, upskilling, and preparation for workforce demand. Based on these insights, the meth-synthesis proposes a new framework aimed at addressing the identified challenges. The findings of this study have significant implications for enhancing the quality of English language assessment across ASEAN countries.

Eco-labels have gained increasing attention from scholars in the green marketing field. Ecolabels as an indicator of sustainable products are believed to be an effective strategy to change consumer behaviour towards purchasing green products as well as raising awareness towards the concept of sustainability. However, it has not been discovered deeply in Ireland yet. While worldwide theoritical knowledge can be put into use to modern society on a global scale, there is still very little known about the consumers in Ireland especially from the population of millennials. This study aims to investigate the impact of Eco-labels on driving millennial consumers green purchasing behaviour in the food industry in Ireland. It has intended to understand consumer understanding of eco-labels and main behavioural drivers to purchase green products. In this explanatory research to understand the relationship of eco-labels and green consumer behaviour, quantitative research design was used with a deductive approach. The questionnaire was used to find out whether millennial consumers understand variety of eco-labels on packages in food products, and thus if it helps to drive actual behaviour to buy green products. According to findings, the positive impact of eco-labels on purchasing behaviour amongst millennial consumers have been suggested as initiatives which increase the chance of creating a sustainable production chain and preserve the natural environment.

Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified structure of the model, which is defined by the number of classes and, possibly, fixation and equality constraints. The model structure is usually chosen on theoretical grounds. A large variety of structurally different latent class models can be compared using goodness-of-fit indices of the chi-square family, Akaike's information criterion, the Bayesian information criterion, and various other statistics. However, finding the optimal structure for a given goodness-of-fit index often requires a lengthy search in which all kinds of model structures are tested. Moreover, solutions may depend on the choice of initial values for the parameters. This article presents a new method by which one can simultaneously infer the model structure from the data and optimize the parameter values. The method consists of a genetic algorithm in which any goodness-of-fit index can be used as a fitness criterion. In a number of test cases in which data sets from the literature were used, it is shown that this method provides models that fit equally well as or better than the models suggested in the original articles.

Complications in the research into personality disorders may be rooted in the assumption within psychiatric diagnosis that underlying constructs are measured with equally valid observed items without rank or recognition of measurement error. The aim of this paper is to investigate the internal validity of DSM-IV (APA, 2000) paranoid personality disorder while accounting for measurement error and the continuous and categorical nature of the construct. General population data from the British Psychiatric Morbidity Survey (Singleton et al., 2001) was obtained from the Data Archives, University of Essex, England. Information from individuals with responses in the paranoid personality disorder section (n = 8393) of the Structured Clinical Interview for DSM-IV Axis II Disorders (SCID-II; First et al., 1997) screening questionnaire was analysed using confirmatory factor analysis (CFA), item response theory (IRT), latent class analysis (LCA) and latent class factor analysis (LCFA) mixture m...

Schools are sometimes slow to adopt evidencebased strategies for improving the mental health outcomes of students. This study used a discrete-choice conjoint experiment to model factors influencing the decision of educators to adopt strategies for improving children's mental health outcomes. A sample of 1,010 educators made choices between hypothetical mental health practice change strategies composed by systematically varying the four levels of 16 practice change attributes. Latent class analysis yielded two segments with different practice change preferences. Both segments preferred small-group workshops, conducted by engaging experts, teaching skills applicable to all students. Participants expressed little interest in Internet options. The support of colleagues, administrators, and unions exerted a strong influence on the practice change choices of both segments. The Change Ready segment, 77.1 % of the sample, was more intent on adopting new strategies to improve the mental health of students. They preferred that schools, rather than the provincial ministry of education, make practice change decisions, coaching was provided to all participants, and participants received post-training follow-up sessions. The Demand Sensitive segment (22.9 %) was less intent on practice change. They preferred that individual teachers make practice change decisions, recommended discretionary coaching, and chose no post-training follow-up support. This study emphasizes the complex social, organizational, and policy context within which educators make practice change decisions. Efforts to disseminate strategies to improve the mental health outcomes of students need to be informed by the preferences of segments of educators who are sensitive to different dimensions of the practice change process. In the absence of a broad consensus of educators, administrators, and unions, potentially successful practice changes are unlikely to be adopted.

This chapter depicts the first case study of the BDSM community in Johannesburg using as evidence an insider’s knowledge and experience of this community.
The aim of this chapter is to provide a sympathetic ear to the BDSM community in Johannesburg.
My objectives in this chapter are:
1.
To find out how the BDSM community in Johannesburg is configured.
2.
To find out the gender and racial composition of the BDSM community in Johannesburg.
To answer these questions, and using various lenses drawn from queer theory, I use the data gleaned from an interview with one of the leading members of this community. I begin this chapter by overviewing the South African literature on BDSM followed by a description of the theoretical framework that I use to shine a light on the data. I then explain how the data was collected and then I present an analysis of the data. I conclude this chapter by referring to my major findings about the BDSM scene in Johannesburg.

ObjectivesTo classify South African adults with chronic health conditions for multimorbidity (MM) risk, and to determine sociodemographic, anthropometric and behavioural factors associated with identified patterns of MM, using data from the WHO’s Study on global AGEing and adult health South Africa Wave 2.DesignNationally representative (for ≥50-year-old adults) cross-sectional study.SettingAdults in South Africa between 2014 and 2015.Participants1967 individuals (men: 623 and women: 1344) aged ≥45 years for whom data on all seven health conditions and socioeconomic, demographic, behavioural, and anthropological information were available.MeasuresMM latent classes.ResultsThe prevalence of MM (coexistence of two or more non-communicable diseases (NCDs)) was 21%. The latent class analysis identified three groups namely: minimal MM risk (83%), concordant (hypertension and diabetes) MM (11%) and discordant (angina, asthma, chronic lung disease, arthritis and depression) MM (6%). Using t...

Rather than testing a particular hypothesis or set of hypotheses, the study was designed to provide longitudinal information on a broad range of factors known to be associated with children&#39;s health and development, including the neighborhood conditions, economic conditions, parents&#39; health and mental health, parents‟ marital status and the quality of parental relationships, parents&#39; use of public programs, the availability of social support, and parent-child relationships. As such, the Study provides data that are relevant to a large number of questions and serves as a valuable resource for researchers interested in the life chances of children growing up in disadvantaged families.

This study&#39;s objective is to differentiate possible ADHD syndromes on the basis of symptom trajectories, prognosis, and associated clinical features in a high-risk cohort. Latent class analysis of inattentive (IA) and hyperactive-impulsive (HI) symptoms in 387 non-disabled members of a regional low birthweight/preterm birth cohort who were evaluated for ADHD at 6, 9, and 16 years. Adolescent functional outcomes and other clinical features were examined across the classes. Three latent classes were identified: unaffected (modest IA and HI symptom prevalences at six, remitting by nine), school age limited (relatively high IA and HI symptom prevalences at six and nine, declining by 16), and persistent inattentive (high IA and HI prevalences at six and nine, with high IA levels persisting to 16). The persistent inattentive class was distinctively associated with poor functioning, motor problems, other psychiatric disorders, and social difficulties as indexed by a positive screen for...

This paper is a systematic review of the methodology for person fit research targeted specifically at methodologists in training. I analyze the ways in which researchers in the area of person fit have conducted simulation studies for parametric and nonparametric unidimensional IRT models since the seminal review paper by . I specifically review how researchers have operationalized different types of aberrant responding for particular testing conditions in order to compare these simulation design characteristics with features of the real-life testing situations for which person fit analyses are officially reported. I discuss the alignment between the theoretical and practical work and the implications for future simulation work and guidelines for best practice.

BACKGROUND: Electronic cigarettes (e-cigarettes) are now the most commonly used tobacco product among US youth. The extent to which perceptions of e-cigarettes' harm and addictiveness differ from those of other products remains unknown, as does whether these perceptions have changed over time. METHODS: Data from the 2012 and 2014 National Youth Tobacco Survey, a repeated cross-sectional survey of grade 6 to 12 students, were used. Cross-tabulations and logistic regression models were used to describe correlates of perceptions of harm and addictiveness of e-cigarettes, cigars, and smokeless tobacco compared with cigarettes. Trends in perceptions of e-cigarettes' harm among different demographic groups were also assessed. In 2014, 73.0% believed that e-cigarettes were less harmful than cigarettes, compared with 20.2% for smokeless tobacco and 25.8% for cigars. By comparison, 47.1% believed that e-cigarettes were less addictive than cigarettes, compared with only 14.0% for smokeless tobacco and 31.5% for cigars. Use of each product was associated with a perception of decreased harm and addictiveness in adjusted analyses, as was being male, being a non-Hispanic white, and residing with a household member who used that product. Between 2012 and 2014, increasing numbers of US youth thought they were able to assess the relative harm of e-cigarettes and increasingly believed that e-cigarettes are less harmful than cigarettes. Most US youth view e-cigarettes as less harmful and addictive than cigarettes. Far fewer think similarly about cigars and smokeless tobacco. Increases in e-cigarettes' perceived safety mirrors rapid increases observed in their use. Perceived safety correlates with use of each tobacco product.

Background: Clinical presentations of child and adolescent psychopathology can vary systematically for boys and girls. While network analysis is increasingly being applied to explore gender differences in psychopathology among adults, there is a dearth of network studies considering differences in symptoms for boys and girls, particularly in developmental traumarelated symptomatology. Methods: This study involves rural children (n = 375, 39.47% girls) and adolescents (n = 291, 51.20% girls) involved with child protection services in Ontario, Canada. Caregivers completed the Assessment Checklist for Children or Adolescents within the first six months of care. Psychometric network analyses were conducted using subscales for boys and girls. Gender differences were examined via network comparison permutation tests, moderated network models, and independent t-tests. Results: Attachment-related interpersonal difficulties were the most central nodes in the child and adolescent networks for both boys and girls. Emotional dysregulation also had high strength centrality for adolescents. While network comparison tests found the overall network structures and global network strength to be invariant between genders for children and adolescents, moderated network models and independent t-tests revealed several gender differences with regards to the expression of various symptoms. Among children, girls exhibited more indiscriminate and pseudomature interpersonal behaviors, whereas boys expressed significantly more non-reciprocal interpersonal behaviors and self-injury. Adolescent girls exhibited more behavioral dysregulation and suicide discourse in the moderated network model; t-tests also indicated higher levels of emotional dysregulation, negative self-image, and other items. Discussion: This study supports evidence of gender differences in the expression of complex trauma symptomatology among girls and boys across development, including that girls tend to exhibit more symptoms. Findings demonstrate the primacy of attachment-specific difficulties and emotion dysregulation, consistent with the transdiagnostic conceptualization of the consequences of developmental trauma. • Previous research indicates differential expressions of complex trauma among boys and girls, but limited work has examined whether the interrelationship between symptoms differ between boys and girls. • Consistent with previous research, the present study found that girls, regardless of developmental stage, tend to exhibit more symptoms than boys. • The structure of complex trauma symptom networks is invariant between boys and girls in childhood and adolescence. • Clinical assessment and treatment should use validated, developmentally appropriate measures of complex trauma symptomatology, which include measures of attachment security and emotional dysregulation. Further, the centrality of attachment-specific symptoms and emotional dysregulation indicate that interventions that target attachment security and emotion regulation may be particularly potent.

This article analyzes differences in life trajectories in Chilean young people (men and women) entering adulthood (ages 18-29). Using data from the Tenth National Survey on Youth and latent class analysis, we identify seven types of transition to adult life based on sociodemographic variables that the literature establishes as markers of adulthood, such as financial independence and having children and being head of household among others. Our results show that a reduced proportion of young people have all the social markers of adulthood, suggesting that most youngsters do not fully assume adult roles until they reach the fourth decade of their lives. In a similar vein, data show that most youngsters aged 18 to 29 live with their parents and/or are still enrolled in education. We also identify differences by sex, showing that the roles of women as caregivers of children are important in the diversification of young people's life trajectories. Such a transformation in Chile's socio-demographic structure has a direct impact on key public policy issues, including young people's access to housing, falling fertility rates and the adequate age of retirement.

Introducción: El dolor torácico representa una de las principales causas de consulta al servicio de urgencias; por ello la identificación de situaciones que ponen en riesgo la vida, en especial los síndromes coronarios agudos (SCA), se convierte en la prioridad. Las escalas de Braunwald y TIMI son dos de las aproximaciones usadas en la clasificación inicial de los pacientes.Metodología: A partir de una base de datos obtenida de un estudio de la aplicación de rutas críticas en el diagnóstico de los SCA, integrada por pacientes con dolor torácico, se realizó un estudio exploratorio en el que, a partir de un análisis de clases latentes, se evaluaron los componentes de dichas escalas. Resultados: Se encuentra que el mejor modelo consta de dos clases latentes para el caso de la escala de Braunwald y de tres para el TIMI. Se sugiere que podríamos disminuir la dimensionalidad de la escala de Braunwald excluyendo las variables de edema pulmonar y la inversión aislada de la onda T en una der...

Gaming disorder is not yet recognized as a formal psychiatric disorder, and consensus is still lacking in the field concerning the definition of gaming disorder and what methods should be used to measure it. In order to deal with methodological challenges related to previously suggested approaches, the aim of the present study was to develop an alternative assessment procedure for gaming disorder using a latent class cluster approach, and to compare the criterion validity of this procedure with existing assessment procedures. A representative sample of 3,000 adolescents (n = 1,500 female) aged 17.5 years was drawn from the National Registry, and 2,055 participants responded (yielding a response rate of 70.3%). The Gaming Addiction Scale for Adolescents was used to measure gaming disorder and measures of loneliness, anxiety, depression, and aggression were used to test criterion validity. A model with five Latent Class Clusters represented the best fit [BIC(LL) = 21,253,7; L 2 = 3,881,204; df = 1,978; Class. Err. = 0.1239]. The five different groups were labeled never symptoms (46.2%), rarely symptoms (22.3%), occasionally symptoms (23.5%), problem gamers (6.9%), and disordered gamers (1.2%). The groups displayed different probabilities of responses (never/rarely/sometimes/often/very often) to the seven Gaming Addiction Scale items. Regarding criterion validity, MANOVA revealed a significant overall main effect of latent classes [F (20,6359) = 13.50, p < 0.001; Wilks Lambda = 0.871]. All dependent variables (loneliness, depression, anxiety, verbal, and physical aggression) reached statistical significance when results from the dependent variables were considered separately. Comparing the present approach with previous suggested classifications of gaming addiction offered by Lemmens et al. and Charlton and Danforth, the present approach showed greater specificity in terms of number of classes identified. We conclude that the Latent Class approach identifying five different groups of gamers offers a more refined view on addiction compared to previous assessment procedures.

Before joining the doctoral program he worked for nine years at the faculty development office of King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. In this role he was involved in several faculty development activities, particularly working with the faculty members for exploring the use of web-based technologies in the support of classroom teaching. He received his MS in Civil Engineering from KFUPM while he has also earned an MPBL degree from Aalborg University, Denmark. His research focus during his doctoral studies is on institutional and faculty development in engineering education.

Official data that are generated by the National Statistical Institutes (NSIs) has an important role to play in the economic and social decision-making phase of government. Tackling official data using data mining (DM) techniques is key to discovering new information and hidden patterns rather than traditional statistical approaches. While DM techniques are useful in the field of official statistics, the discovery of new DM techniques remains. Data from the 2015 Turkish Statistical Institute (TurkStat) Survey of Income and Living Conditions (SILC) were analyzed using DM techniques in this study. Cross-sectional data were processed for 36036
individuals and the variables influencing the individual income as well as
individual welfare status were identified. Latent class analysis (LCA) and
clustering of k-modes have been applied to assess the individuals ' socioeconomic profiles. Models of clustering and random forest (RF) algorithms have been used to classify the socio-economic status of individuals. In the ten-class LCA model, what class of probability belongs to the newly selected individual has been determined. In the latent classes determined, the latent class profile descriptions of the individuals were derived on the basis of the values provided by the variable values at the highest probability. Ten clusters that were obtained as a consequence
of k-modes clustering were identified by cluster modes, and individual cluster profile descriptions were obtained, and their results were also compared to the LCA results. In this study, which considered categorical variables, it was observed that the LCA method yielded more consistent results than the method k-modes. The importance of the variables was calculated when the individual income was selected in the RF model as a component of all nine input variables. Variables of education, occupation and age have been observed to be more significant and have contributed the most to the RF model, respectively. Methods like LCA and RF appear to be suitable for applying DM and extracting useful results from SILC data, which are comprehensive and detailed data. Similar DM processes for different official data can be used to achieve useful results.

A number of choice experiments (CEs) studies have shown that survey respondents employ heuristics such as attribute non-attendance (ANA) while evaluating food. This paper addresses a set of methodological questions. First, it explores if ANA is an issue to take into account in food valuation studies. Second, it assesses if there is any difference in terms of welfare estimates between the two common ways of collecting self-reported stated ANA (serial and choice task). Next, it validates the statements of ANA behavior provided by the respondents across serial and choice task self-reported ANA. Lastly, it explores the issue of concordance between the stated ANA and inferred ANA methods. We estimated a set of choice models including inferred or observed ANA information. Our results show a clear winner between the two stated approaches, choice task, which also better matches the inferred ANA data.

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO 2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO 2 and food miles valuations are much correlated. CO 2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO 2 label at least as much and sometimes more than the food miles label.

Background: Our study aimed to understand the effects of HIV and cocaine dependence (CD) on discrete aspects of executive functioning via the Stroop Color-Word Test and the Trail Making Test (TMT). We recruited 101 participants (26 HIV+/CD+; 18 HIV+/CD-; 30 HIV-/CD+; and 27 HIV-/CD-. Methods: We utilized a series of 2 (HIV: yes/no) × 2 (Cocaine: yes/no) ANCOVA’s while controlling for age and premorbid intelligence on the Stroop trials (i.e., color-naming, word reading, interference), and ANOVA’s were used to test for group differences on TMT-A and TMT-B z-scores, the number of errors, and the B/A ratio score. Results: We found a significant main effect of HIV on the Stroop Interference (p = 0.012) and the TMT B/A ratio (p = 0.017), these findings are consistent with difficulties in cognitive flexibility. On the Color-Naming and Interference trials, individuals with CD made significantly more errors than non-users (p = 0.028), demonstrating difficulties with inhibition. Conclusions: ...

The workplace is a captive environment where the overall contribution of the meal served could be an important element of the overall diet. Despite growing demand little information is available to aid healthy dish selection. This study identifies information valued by consumers in the UK, Greece, Denmark and France using best-worst scaling. Value for Money, Nutrition and Naturalness are key elements of information that consumers require to be able to make a conscious decision about dish selection in all four countries. Latent class analysis shows that consumers align to one of five cluster groups, i.e., Value Driven, Conventionalists, Socially Responsible, Health Conscious and Locavores. Understanding key information needs can allow food operators to align their service with consumer preferences across different market segments.

The resilience of Southeast Asian farming cultures is closely linked to personal and familial commitments, emotional connections to agricultural livelihoods, spirituality, and cultural values. This paper explores the heritage ricescapes of Bali (Indonesia) and Ifugao (Philippines), investigating how these intangible sources, collectively termed the "Is," contribute to the resilience-building strategies of Indigenous rice farmers through affective relationships. Utilising a mixed-methods approach that combines survey data with qualitative insights from interviews and focus groups, the study identifies four critical "Is": Personal and Family Commitment, Continuity of Rice Farming and Livelihood Security, Adaptation in Practices, and Personal Beliefs and Spirituality. These elements significantly influence resilience within these agricultural communities. The survey analysis, employing Latent Class Analysis, reveals distinct subgroups of farmers based on their varied utilisation of the "Is," highlighting the diversity in resilience strategies. This classification enhances our understanding of how different farmer subgroups respond to challenges, informing the development of targeted interventions. The findings emphasise that resilience is not solely dependent on tangible resources but is profoundly shaped by social, cultural, and spiritual dimensions and the affective relationships that underpin them. Future research should focus on longitudinal studies to investigate the evolution of resilience strategies and consider integrating participatory action research methods to empower farmers and enhance community engagement. This research aims to inform policies and practices that strengthen resilience and sustainability in agricultural contexts, particularly regarding emerging hazards that threaten Indigenous rice cultivation in World Heritage sites.

The associations between empirically derived dietary habits and irritable bowel syndrome (IBS) have not been investigated. This study aimed to assess the relationship between empirically derived dietary habits and IBS in a large population of Iranian adults. In a cross-sectional study, dietary habits of 4763 adults were assessed in three domains, &quot;meal pattern&quot;, &quot;eating rate&quot; and &quot;intra-meal fluid intake&quot;. We used latent class analysis to identify classes of dietary habits. IBS was defined based on ROME III criteria. IBS was prevalent in 20.3% (n = 966) of the study population. Two distinct classes of meal patterns: &quot;regular&quot; and &quot;irregular&quot;, three classes of eating rates: &quot;moderate&quot;, &quot;moderate-to-slow&quot; and &quot;moderate-to-fast&quot; and two classes of fluid ingestion with meals: &quot;moderate&quot; and &quot;heavy intra-meal drinking&quot; were identified. After adjustment for confounders, &quot;heavy intra-me...

ObjectivesIndonesia implemented its first e-cigarette regulation in 2018, a 57% tax on the retail price of e-cigarette liquid (e-liquid), exceeding the 40% average tax on cigarettes. Economic research suggests that this tax could unintentionally increase cigarette smoking among dual users, but this has not been examined in a low-income or middle-income country. We therefore investigated the effects of the e-liquid tax among adults in Indonesia.DesignPre–post study.SettingIndonesia.ParticipantsAdults who currently used e-cigarettes and either currently or occasionally smoked cigarettes or recently quit were recruited using Facebook and Instagram ads. Our follow-up response rate was 79%. A final sample of 1039 adults participated.Primary outcome measuresE-cigarette and cigarette use.ResultsFollowing the e-liquid tax, participants reported paying a 4.4% higher price for e-liquid (p=0.02). Participants also reported an average 0.5-day decrease in the number of days they used e-cigarette...

Background/aim: The aim of this study is to assess the Xpert MTB/RIF assay for diagnosis of the Mycobacterium tuberculosis complex in clinical samples and to compare the results by reference to the diagnostic method, Bactec MGIT 960. A total of 7407 samples were included from patients not primarily suggesting pulmonary or extrapulmonary tuberculosis (TB), collected from patients required to be screened for TB and excluding TB diagnoses since it was a differential diagnosis. Also included were a total of 411 samples from patients primarily suggesting pulmonary or extrapulmonary TB. In the first group, 152 of 7407 samples yielded positive results with the Bactec MGIT 960, 131 (1.77%) were found positive with Löwenstein-Jensen medium, and 295 (3.99%) were found positive with Ziehl-Neelsen staining. In the second group, 24 (5.8%), 17 (4.1%), and 28 (6.8%) of 411 samples were found positive. Xpert MTB/RIF [27 (6.6%) of 411 samples] detected 3 additional samples as positive, and these 3 cases were clinically compatible with TB. The Xpert MTB/RIF assay shows superior performance for the diagnosis of TB. Its usefulness in culture-negative patients and the best method for integrating this diagnostic method into current tuberculosis diagnostic algorithms both need further study.

Parricide is a rare type of homicide in which mental illness is often an important factor. The aims of this study were (a) to describe the characteristics of parricide offenders with a focus on mental illness and clinical care and (b) to examine Heide's widely used typology of parricide through a data-driven approach. We analyzed all homicides in England and Wales between 1997 and 2014. Parricide offenders in our sample were most often male, unmarried, and unemployed, with a third of offenders diagnosed with schizophrenia; 28% had been in contact with mental health services before the offense. The latent class analysis resulted in three types of parricide offenders: middle-aged with affective disorder, previously abused, and seriously mentally Ill, which confirmed, to an extent, Heide's typology. Health and social care services should actively engage with carers of people with mental illness and support to those caring for older relatives and victims of abuse.

Parricide is a rare type of homicide in which mental illness is often an important factor. The aims of this study were (a) to describe the characteristics of parricide offenders with a focus on mental illness and clinical care and (b) to examine Heide&#39;s widely used typology of parricide through a data‐driven approach. We analyzed all homicides in England and Wales between 1997 and 2014. Parricide offenders in our sample were most often male, unmarried, and unemployed, with a third of offenders diagnosed with schizophrenia; 28% had been in contact with mental health services before the offense. The latent class analysis resulted in three types of parricide offenders: middle‐aged with affective disorder, previously abused, and seriously mentally Ill, which confirmed, to an extent, Heide&#39;s typology. Health and social care services should actively engage with carers of people with mental illness and support to those caring for older relatives and victims of abuse.

Background and Aims: This study examines the association of mental health, social and relational contexts, and gaming-related characteristics on the psychological profiles of video game players based on emotional regulation and motivations for gaming. Methods: A multinomial logistic regression analysis was conducted on an international sample of 5.255 gamers aged 16 to 69 (M = 25.6 years, SD = 6.46). Participants included 49.87 % men (M = 26.4, SD = 7.06), 43.24 % women (M = 25.1, SD = 5.77), and 9.29 % non-binary individuals (M = 23.3, SD = 5.24) from 112 countries. Mental health, attachment styles, social interactions, and gaming behaviors were analyzed into four profiles: avoidant, engaged, relational, and dysregulated. Results: The avoidant profile, linked to older gamers, exhibited low distress, secure attachment, and offline social preferences, reflecting healthier habits. The engaged profile, the largest group, showed secure attachment and active integration of gaming into social contexts. The relational profile presented insecure attachment and emotional regulation difficulties. The dysregulated profile, associated with younger gamers, was characterized by high distress, emotional dysregulation, substance use, and a preference for online interactions. Conclusions: The profiles dysregulated and relational are associated with insecure attachment and mental health difficulties, whereas the profiles engaged and avoidant are associated with secure attachment and low levels of psychological distress. These findings underscore the complex interplay of psychological, social, and gamingrelated factors associated with gaming profiles, offering insights for further study on harm prevention and promoting non-problematic gaming behaviors.

Depression is a significant public health problem but symptom remission is difficult to predict. This may be due to substantial heterogeneity underlying the disorder. Latent class analysis (LCA) is often used to elucidate clinically relevant depression subtypes but whether or not consistent subtypes emerge is unclear. We sought to critically examine the implementation and reporting of LCA in this context by performing a systematic review to identify articles detailing the use of LCA to explore subtypes of depression among samples of adults endorsing depression symptoms. PubMed, PsycINFO, CINAHL, Scopus, and Google Scholar were searched to identify eligible articles indexed prior to January 2016. Twenty-four articles reporting 28 LCA models were eligible for inclusion. Sample characteristics varied widely. The majority of articles used depression symptoms as the observed indicators of the latent depression subtypes. Details regarding model fit and selection were often lacking. No consistent set of depression subtypes was identified across studies. Differences in how models were constructed might partially explain the conflicting results. Standards for using, interpreting, and reporting LCA models could improve our understanding of the LCA results. Incorporating dimensions of depression other than symptoms, such as functioning, may be helpful in determining depression subtypes.

Emergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.

Latent class models offer an alternative perspective to the popular mixed logit form, replacing the continuous distribution with a discrete distribution in which preference heterogeneity is captured by membership of distinct classes of utility description. Within each class, preference homogeneity is usually assumed (i.e., fixed parameters), although interactions with observed contextual effects are permissible. A natural extension of the fixed parameter latent class model is a random parameter latent class model which allows for another layer of preference heterogeneity within each class. This paper sets out the random parameter latent class model, building on the fixed parameter latent class model, and illustrates its applications using a stated choice data set on alternative freight distribution attribute packages pivoted around a recent trip in Australia.

Many college students experience personal consequences from their own substance use as well as secondhand effects resulting from other students' substance use. Our study identifies meaningful subgroup response patterns representing the construct of experienced harms, that is, the combined harms resulting from personal substance use and the substance use of others. In this sample six latent classes of harms experienced by participants were identified. The classes ranged from a No Harms group to a group of eleven harms -Severe Harms. We demonstrated that harms class membership was directly related to the level of involvement with substances. As the level of substance use increaseddemonstrated by membership in latent classes of progressive involvement with substancesthe odds of membership in a more serious experienced harms class increased. Participants reporting early onset of any substance were more likely to be members in any of the experienced harms latent classes than members of the No Harms class. Elucidating the exposure to harm associated with college student substance use behavior through an expanded focus on the patterns of experienced effects (i.e., personal consequences and secondhand effects) advances current research on a nationally-recognized problem.

Many college students experience personal consequences from their own substance use as well as secondhand effects resulting from other students' substance use. Our study identifies meaningful subgroup response patterns representing the construct of experienced harms, that is, the combined harms resulting from personal substance use and the substance use of others. In this sample six latent classes of harms experienced by participants were identified. The classes ranged from a No Harms group to a group of eleven harms -Severe Harms. We demonstrated that harms class membership was directly related to the level of involvement with substances. As the level of substance use increaseddemonstrated by membership in latent classes of progressive involvement with substancesthe odds of membership in a more serious experienced harms class increased. Participants reporting early onset of any substance were more likely to be members in any of the experienced harms latent classes than members of the No Harms class. Elucidating the exposure to harm associated with college student substance use behavior through an expanded focus on the patterns of experienced effects (i.e., personal consequences and secondhand effects) advances current research on a nationally-recognized problem.

To investigate the combinations of Musculoskeletal pain (MSP) (neck, shoulder, upper and low back pain) among a sample of Iranian school children. The MSP combinations was modeled by latent class analysis (LCA) to find the clusters of high-risk individuals and multigroup LCA taking into account the gender and age (≤ 13 years and ≥ 14 years of age categories). The lowest and highest prevalence of MSP was 14.2% (shoulder pain in boys aged ≥14 years) and 40.4% (low back pain in boys aged ≤13 years), respectively. The likelihood of synchronized neck and low back pain (9.4-17.7%) was highest, while synchronized shoulder and upper back pain (4.5-9.4%) had the lowest probability. The probability of pain at three and four locations was significantly lower in boys aged ≥14 years than in other gender-age categories. The LCA divided the children into minor, moderate, and major pain classes. The likelihood of shoulder and upper back pain in the major pain class was higher in boys than in girls,...

Cet article explore l'évolution du stress en milieu professionnel, autrefois perçu comme une menace pour la santé, aujourd'hui valorisé comme un indicateur de performance. Dans un contexte où compétitivité et efficacité dominent, la capacité à gérer le stress est devenue une compétence recherchée. Cependant, cette valorisation du stress présente des risques significatifs pour la santé mentale et physique des employés, posant un défi pour les pratiques de gestion et la sociologie de la santé au travail. À travers des entretiens semi-structurés avec des cadres et ouvriers, l'étude révèle que, bien qu'un stress modéré puisse temporairement améliorer la performance, sa normalisation comme critère de succès mène à des conséquences délétères, telles que le burnout et des maladies cardiovasculaires. Cette recherche met également en lumière une accentuation des inégalités, où seuls ceux capables de supporter un stress chronique obtiennent des récompenses, au détriment des autres. L'article questionne les normes sociales légitimant cette culture du stress et les effets à long terme sur le bien-être des travailleurs.

Recent developments in latent class (LC) analysis and associated software to include continuous variables offer a model-based alternative to more traditional clustering approaches such as K-means. In this paper, the authors compare these two approaches using data simulated from a setting where true group membership is known. The authors choose a setting favourable to K-means by simulating data according to the assumptions made in both discriminant analysis (DISC) and K-means clustering. Since the information on true group membership is used in DISC but not in clustering approaches in general, the authors use the results obtained from DISC as a gold standard in determining an upper bound on the best possible outcome that might be expected from a clustering technique. The results indicate that LC substantially outperforms the K-means technique. A truly surprising result is that the LC performance is so good that it is virtually indistinguishable from the performance of DISC.

Recent developments in latent class (LC) analysis and associated software to include continuous variables offer a model-based alternative to more traditional clustering approaches such as K-means. In this paper, the authors compare these two approaches using data simulated from a setting where true group membership is known. The authors choose a setting favourable to K-means by simulating data according to the assumptions made in both discriminant analysis (DISC) and K-means clustering. Since the information on true group membership is used in DISC but not in clustering approaches in general, the authors use the results obtained from DISC as a gold standard in determining an upper bound on the best possible outcome that might be expected from a clustering technique. The results indicate that LC substantially outperforms the K-means technique. A truly surprising result is that the LC performance is so good that it is virtually indistinguishable from the performance of DISC.